The present invention relates to a method for calibrating a coordinate measuring machine and to a coordinate measuring machine where such a method is implemented.
Coordinate measuring machines have a sensor that can move relative to a measurement object. The measurement object is typically placed on a measuring table or another suitable reception. The sensor is brought into a defined position relative to the measurement object. Subsequently, spatial coordinates of defined measuring points are determined on the measurement object by evaluating the position of the sensor in the measuring volume and, if appropriate, further measured data supplied by the sensor. Such a coordinate measuring machine can be used to determine geometric dimensions including shape and contour profiles of the measurement object by picking up the spatial coordinates at a plurality of measuring points. A typical application for coordinate measuring machines is therefore in quality control of workpieces.
In many cases, coordinate measuring machines have a so-called tactile measuring sensor. This is a sensor having a sensor base that can be moved relative to the measurement object. The sensor further has a probe element, often in the form of a probe pin by means of which contact with a measuring point on the measurement object is made. The probe element can move relative to the sensor base such that it is deflected during contact of a measuring point. Measuring elements in the sensor serve for determining these deflections relative to the sensor base in order to enable a high measuring accuracy. As a rule, the deflections of the probe element relative to the sensor base are transformed using a so-called transformation matrix into a coordinate system that specifies the position of the sensor in the measuring volume. The coefficients of the transformation matrix are calculated in a calibration operation, wherein reference measured values are picked up on a reference measurement object having known properties.
EP 1 051 596 B1 discloses such a calibration method, wherein the position and the radius of a probe ball arranged on the end of the probe pin are determined first, and wherein the coefficients of the transformation matrix are subsequently calculated. The method according to EP 1 051 596 B1 furthermore provides that a plurality of further reference measured values are used to determine an error table that represents measurement deviations as a function of the magnitude of the deflection of the probe element and as a function of the respective measuring position. This error table can be provided in the form of a so-called look-up table or, alternatively, in the form of a polynomial function with polynomial coefficients. In the latter case, the polynomial function serves for correcting nonlinear measurement deviations by computing a linearization for the nonlinear behavior of the sensor system with the aid of the polynomial function.
Consequently, calibration includes not only the determination of the coefficients for the transformation matrix, but also the determination of suitable polynomial coefficients that represent the remaining, nonlinear measurement deviations.
The method according to EP 1 051 596 B1 requires a high number of reference measured values and is therefore rather time-consuming. This is disadvantageous, because it is often necessary to repeat a calibration during operation of the coordinate measuring machine in order to enable high accuracy measurements.
In order to speed up the calibration of a coordinate measuring machine having a measuring sensor, it is desirable to minimize the number of parameters or coefficients which have to be determined by means of the calibration. The fewer parameters/coefficients need to be determined, the fewer reference measured values are required. On the other hand, minimization should not lead to significant measurement deviations being overlooked.
It has emerged from the search for an improved calibration method that a polynomial transformation for correcting nonlinearities can in part cause intensive measurement deviations at points that are not supported by reference measured values. In other words, a polynomial transformation can cause “new” nonlinear measurement deviations even when the polynomial transformation yields very good correction results at those interpolation points that are supported by reference measured values.